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  1. 00280/img-mean-std-00280011.npy +3 -0
  2. 00280/img-mean-std-00280016.npy +3 -0
  3. 00280/img-mean-std-00280023.npy +3 -0
  4. 00280/img-mean-std-00280024.npy +3 -0
  5. 00280/img-mean-std-00280035.npy +3 -0
  6. 00280/img-mean-std-00280040.npy +3 -0
  7. 00280/img-mean-std-00280047.npy +3 -0
  8. 00280/img-mean-std-00280049.npy +3 -0
  9. 00280/img-mean-std-00280051.npy +3 -0
  10. 00280/img-mean-std-00280056.npy +3 -0
  11. 00280/img-mean-std-00280058.npy +3 -0
  12. 00280/img-mean-std-00280072.npy +3 -0
  13. 00280/img-mean-std-00280075.npy +3 -0
  14. 00280/img-mean-std-00280080.npy +3 -0
  15. 00280/img-mean-std-00280087.npy +3 -0
  16. 00280/img-mean-std-00280089.npy +3 -0
  17. 00280/img-mean-std-00280091.npy +3 -0
  18. 00280/img-mean-std-00280096.npy +3 -0
  19. 00280/img-mean-std-00280098.npy +3 -0
  20. 00280/img-mean-std-00280100.npy +3 -0
  21. 00280/img-mean-std-00280109.npy +3 -0
  22. 00280/img-mean-std-00280111.npy +3 -0
  23. 00280/img-mean-std-00280116.npy +3 -0
  24. 00280/img-mean-std-00280118.npy +3 -0
  25. 00280/img-mean-std-00280132.npy +3 -0
  26. 00280/img-mean-std-00280135.npy +3 -0
  27. 00280/img-mean-std-00280163.npy +3 -0
  28. 00280/img-mean-std-00280164.npy +3 -0
  29. 00280/img-mean-std-00280172.npy +3 -0
  30. 00280/img-mean-std-00280175.npy +3 -0
  31. 00280/img-mean-std-00280189.npy +3 -0
  32. 00280/img-mean-std-00280198.npy +3 -0
  33. 00280/img-mean-std-00280201.npy +3 -0
  34. 00280/img-mean-std-00280206.npy +3 -0
  35. 00280/img-mean-std-00280208.npy +3 -0
  36. 00280/img-mean-std-00280217.npy +3 -0
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  38. 00280/img-mean-std-00280222.npy +3 -0
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  40. 00280/img-mean-std-00280248.npy +3 -0
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  48. 00280/img-mean-std-00280301.npy +3 -0
  49. 00280/img-mean-std-00280317.npy +3 -0
  50. 00280/img-mean-std-00280319.npy +3 -0
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